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Snowflake is about empowering enterprises to achieve their full potential u2014 and people too. With a culture that's all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology u2014 and careers u2014 to the next level.
We are looking for people who have a strong background in data science and cloud architecture to join our AI/ML Workload Services team to create exciting new offerings and capabilities for our customers! This team within the Professional Services group will be working with customers using Snowflake to expand their use of the Data Cloud to bring data science pipelines from ideation to deployment, and beyond using Snowflake's features and its extensive partner ecosystem. The role will be highly technical and hands-on, where you will be designing solutions based on requirements and coordinating with customer teams, and where needed Systems Integrators.
Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload
Build, deploy and ML pipelines using Snowflake features and/or Snowflake ecosystem partner tools based on customer requirements
Work hands-on where needed using SQL, Python, and APIs to build POCs that demonstrate implementation techniques and best practices on Snowflake technology for GenAI and ML workloads
Follow best practices, including ensuring knowledge transfer so that customers are properly enabled and are able to extend the capabilities of Snowflake on their own
Maintain deep understanding of competitive and complementary technologies and vendors within the AI/ML space, and how to position Snowflake in relation to them
Work with System Integrator consultants at a deep technical level to successfully position and deploy Snowflake in customer environments
Provide guidance on how to resolve customer-specific technical challenges
Support other members of the Professional Services team develop their expertise
Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake's products and marketing
Ability and flexibility to travel to work with customers on-site 25% of the time
Minimum 10 years experience working with customers in a pre-sales or post-sales technical role
Skills presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos
Thorough understanding of the complete Data Science life-cycle including feature engineering, model development, model deployment and model management.
Strong understanding of MLOps, coupled with technologies and methodologies for deploying and monitoring models
Experience and understanding of at least one public cloud platform (AWS, Azure or GCP)
Experience with at least one Data Science tool such as Sagemaker, AzureML, Vertex, Dataiku, DataRobot, H2O, and Jupyter Notebooks
Experience with Large Language Models, Retrieval and Agentic frameworks
Hands-on scripting experience with SQL and at least one of the following Python, R, Java or Scala.
Experience with libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn or similar
University degree in computer science, engineering, mathematics or related fields, or equivalent experience
Experience with Generative AI, LLMs and Vector Databases.
Experience with Databricks/Apache Spark, including PySpark
Experience implementing data pipelines using ETL tools
Experience working in a Data Science role
Proven success at enterprise software
Vertical expertise in a core vertical such as FSI, Retail, Manufacturing etc.
Snowflake is growing fast, and we're scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information:
Snowflake Inc. is a cloud computing–based data warehousing company based in Bozeman, Montana. It was founded in July 2012 and was publicly launched in October 2014 after two years in stealth mode. The firm offers a cloud-based data storage and analytics service, generally termed "data warehouse-as-a-service".
Job ID: 134147753